In-Center Hemodialysis and Patient Travel Time in Aotearoa New Zealand: A Nationwide Geospatial and Data Linkage Study
Introduction: Prolonged travel time to receive dialysis is associated with decreased quality of life and increased mortality. However, patient travel time is rarely systematically analyzed during health service planning. This study’s aims were as follows: (i) examine spatio-temporal trends in travel...
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| Main Authors: | , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2025-03-01
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| Series: | Kidney International Reports |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2468024924034740 |
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| Summary: | Introduction: Prolonged travel time to receive dialysis is associated with decreased quality of life and increased mortality. However, patient travel time is rarely systematically analyzed during health service planning. This study’s aims were as follows: (i) examine spatio-temporal trends in travel time for people commencing dialysis in Aotearoa New Zealand (NZ), (ii) assess the relationship between travel time and dialysis modality, and (iii) create interactive nationwide maps to support renal service planning. Methods: AcceSS and Equity in Treatment for kidney disease (ASSET), a health-linked data platform, was used to include all people commencing dialysis in NZ from 2006 to 2019 (N = 6690). Patients’ one-way driving times from their residential location to the nearest hemodialysis unit were estimated using geospatial software. Multiple logistic regression modelling explored the association between travel time and dialysis modality, adjusting for demographic, clinical, and service factors. Results: Median one-way driving time was 14 minutes (interquartile interval [IQI]: 8–31) and was significantly higher for patients living in rural (45 minutes [IQI: 28–62]) than in urban areas (11 minutes [IQI:8–18]; P < 0.001). Patients living farther from a unit were independently less likely to receive in-center hemodialysis (0.62 [95% confidence interval, CI: 0.52–0.72] for driving time ≥ 30 minutes; odds ratio, OR: 0.82 [95% CI:0.68–0.99] for 20–29; reference < 10), as were those in regions with greater hemodialysis unit capacity pressure. Our interactive maps demonstrate marked interregional variation in dialysis modality, patient travel time, and unit capacity. Conclusion: Innovative service design is needed to reduce the burden of travel time, particularly for rural dialysis patients. We present novel geospatial techniques to support dialysis service planning that is targeted to the areas of greatest need. |
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| ISSN: | 2468-0249 |